A5102931860- X-ray Diffraction in Crystallography
- Radiomics and Machine Learning in Medical Imaging
- Advanced Chemical Sensor Technologies
- Medical Imaging Techniques and Applications
- Nuclear Physics and Applications
- Metabolomics and Mass Spectrometry Studies
- Climate variability and models
- Arctic and Antarctic ice dynamics
- Oceanographic and Atmospheric Processes
- Cryospheric studies and observations
- Climate change and permafrost
- Remote Sensing and Land Use
- Meteorological Phenomena and Simulations
- Metal-Organic Frameworks: Synthesis and Applications
- Environmental Changes in China
- Atmospheric and Environmental Gas Dynamics
- Land Use and Ecosystem Services
- Coastal wetland ecosystem dynamics
- Methane Hydrates and Related Phenomena
- Marine and coastal ecosystems
- Soil Moisture and Remote Sensing
- Crystallization and Solubility Studies
- Geophysics and Gravity Measurements
- Atmospheric Ozone and Climate
- Environmental and Agricultural Sciences
Fuzhou University
2016-2025
Ghent University Hospital
2025
Nanjing University
2024
Northwestern Polytechnical University
2023-2024
Nanjing General Hospital of Nanjing Military Command
2024
Chinese Academy of Social Sciences
2019
Central University of Finance and Economics
2018
Xiamen University
2013-2017
Tsinghua University
1999-2016
Beijing Language and Culture University
2016
Groundwater interacts with soil moisture through the exchanges of water between unsaturated and its underlying aquifer under gravity capillary forces. Despite importance, groundwater is not explicitly represented in climate models. This paper developed a simple model (SIMGM) by representing recharge discharge processes storage an unconfined aquifer, which added as single integration element below land surface model. We evaluated against Gravity Recovery Climate Experiment (GRACE) terrestrial...
Thirty‐three snowpack models of varying complexity and purpose were evaluated across a wide range hydrometeorological forest canopy conditions at five Northern Hemisphere locations, for up to two winter snow seasons. Modeled estimates water equivalent (SWE) or depth compared observations open sites each location. Precipitation phase duration above‐freezing air temperatures are shown be major influences on divergence convergence modeled the subcanopy snowpack. When considered collectively all...
Abstract Retrieving the subsurface and deeper ocean (SDO) dynamic parameters from satellite observations is crucial for effectively understanding interior anomalies processes, but it challenging to accurately estimate thermal structure over global scale sea surface parameters. This study proposes a new approach based on Random Forest (RF) machine learning retrieve temperature anomaly (STA) in multisource including height (SSHA), (SSTA), salinity (SSSA), wind (SSWA) via situ Argo data RF...
Urbanization has become one of the most important human activities modifying Earth’s land surfaces; and its impacts on tropical subtropical cities (e.g., in South/Southeast Asia) are not fully understood. Colombo; capital Sri Lanka; been urbanized for about 2000 years; due to strategic position east–west sea trade routes. This study aims investigate characteristics urban expansion surface temperature Colombo from 1988 2016; using a time-series Landsat images. Urban cover changes (ULCC) were...
Subsurface ocean observations are sparse and insufficient, significantly constraining studies of processes. Retrieving high-resolution subsurface dynamic parameters from remote sensing using specific inversion models is possible but challenging. This study proposed two kinds machine learning algorithms, namely, Convolutional Neural Network (CNN) Light Gradient Boosting Machine (LightGBM), to reconstruct the temperature (ST) ocean's upper 1000 m with a high resolution 0.25° based on...
Chlorophyll-a (chl-a) is an important parameter of water quality and its concentration can be directly retrieved from satellite observations. The Ocean Land Color Instrument (OLCI), a new-generation water-color sensor onboard Sentinel-3A Sentinel-3B, excellent tool for marine environmental monitoring. In this study, we introduce new machine learning model, Light Gradient Boosting Machine (LightGBM), estimating time-series chl-a in Fujian’s coastal waters using multitemporal OLCI data situ...
This investigation establishes a multisensor snow data assimilation system over North America (from January 2002 to June 2007), toward the goal of better estimation snowpack (in particular, water equivalent and depth) via incorporating both Gravity Recovery Climate Experiment (GRACE) terrestrial storage (TWS) Moderate Resolution Imaging Spectroradiometer (MODIS) cover fraction (SCF) information into Community Land Model. The different properties associated with SCF TWS observations are...
Retrieving multi-temporal and large-scale thermohaline structure information of the interior global ocean based on surface satellite observations is important for understanding complex multidimensional dynamic processes within ocean. This study proposes a new ensemble learning algorithm, extreme gradient boosting (XGBoost), retrieving subsurface anomalies, including temperature anomaly (STA) salinity (SSA), in upper 2000 m The model combines situ Argo data estimation, uses root-mean-square...
The reconstruction of the ocean’s 3D thermal structure is essential to study ocean interior processes and global climate change. Satellite remote sensing technology can collect large-scale, high-resolution observation data, but only at surface layer. Based on empirical statistical artificial intelligence models, deep techniques allow us retrieve reconstruct temperature by combining observations with in situ float observations. This proposed a new learning method, Convolutional Long...
Subsurface density (SD) is a crucial dynamic environment parameter reflecting 3-D ocean process and stratification, with significant implications for the physical, chemical, biological processes of environment. Thus, accurate SD retrieval essential studying in interior. However, complete spatiotemporally remains challenge terms equation state physical methods. This study proposes novel multiscale mixed residual transformer (MMRT) neural network method to compensate inadequacy existing...
Estimating the ocean mixed layer depth (MLD) is crucial for studying atmosphere-ocean interaction and global climate change. Satellite observations can accurately estimate MLD over large scales, effectively overcoming limitation of sparse in situ reducing uncertainty caused by estimation based on reanalysis data. However, combining multisource satellite to still extremely challenging. This study proposed a novel Residual Convolutional Gate Recurrent Unit (ResConvGRU) neural networks, along...
High‐quality continental‐scale snow water equivalent (SWE) data sets are generally not available, although they important for climate research and resources management. This study investigates the feasibility of a framework developing such needed over North America, through ensemble Kalman filter (EnKF) approach, which assimilates cover fraction observed by Moderate Resolution Imaging Spectroradiometer (MODIS) into Community Land Model (CLM). We use meteorological forcing from Global Data...
To estimate sea ice thickness over a large spatial scale is challenge. In this paper, we propose direct approach to effectively area of the Bohai Sea using EOS MODIS data. It based on model an exponential relation between albedo and ice. Eighteen images L1B data in 2009–2010 winter were used monitor its spatiotemporal evolution Sea. The estimated results are accordance with Lebedev Zubov empirical models as well forecasting from National Marine Environmental Forecasting Centre China. Model...
Abstract Land use and land cover change (LULCC) is primarily characterized as forest conversion to cropland for the development of agriculture. Previous climate modeling studies have demonstrated LULCC impacts on mean its long‐term trends. This study investigates diurnal seasonal climatic response in monsoon Asia through two numerical experiments with potential current vegetation using fully coupled Community Earth System Model. Results show that leads a reduced temperature range due...
The DisTrad (Disaggregation Procedure for Radiometric Surface Temperature) model shows limited applicability sub-pixel mapping of thermal remote-sensing images in densely vegetated areas due to the phenomenon normalized difference vegetation index (NDVI) saturation. In this article, we compared effect NDVI and enhanced (EVI) their different sensitivity areas. Taking Ganzhou Southern China as an example, produced 250-m from a 1000-m image using EVI data. After comparing with synchronous 90-m...
Retrieving information concerning the interior of ocean using satellite remote sensing data has a major impact on studies dynamic and climate changes; however, lack within limits such about global ocean. In this paper, an artificial neural network, combined with gridded Argo product, is used to estimate heat content (OHC) anomalies over four different depths down 2000 m covering near-global ocean, excluding polar regions. Our method allows for temporal hindcast OHC other periods beyond...
As the most relevant indicator of global warming, ocean heat content (OHC) change is tightly linked to Earth’s energy imbalance. Therefore, it vital study OHC and absorption redistribution. Here we analyzed characteristics variations based on a previously reconstructed dataset (named OPEN) with four other gridded datasets from 1993 2021. Different datasets, OPEN directly obtains through remote sensing, which reliable superior in reconstruction, further verified by Clouds Radiant Energy...
We present an improved high-index saddle dynamics (iHiSD) for finding points and constructing solution landscapes, which is a crossover from gradient flow to traditional HiSD such that the Morse theory could be involved. propose analysis reflection manifold in iHiSD, then prove its stable nonlocal convergence outside of region attraction point, resolves dependence on initial value. analyze discretized iHiSD inherits these properties. Furthermore, based theory, we any two connected by...